Orpheus Telugu Male (QLoRA v1)
A Telugu text-to-speech voice, finetuned from Orpheus. Voice prefix:
telugu_male.
Eval loss 3.1779 -- the best figure recorded in this project, below the Tamil full-finetune baseline of 3.235 that had needed a rented A100. This one trained on a single consumer 16 GB card at no GPU cost.
Measured median F0 of generated speech: 136.9 Hz.
See also the matching female voice and the GGUF build.
Model details
| Base | canopylabs/3b-hi-pretrain-research_release (Orpheus, Llama-3.2-3B backbone) |
| Method | QLoRA (4-bit nf4 base, bf16 compute), r=64 alpha=128, attention + MLP; embeddings frozen |
| Schedule | 2 epochs, lr 2e-4 cosine, batch 1 x grad-accum 16 |
| Hardware | one 16 GB RTX 5060 Ti, trained locally |
| Corpus | SYSPIN Telugu (arpit-tiwari/syspin-telugu-tts) -- studio read speech with ground-truth transcripts |
How it works
Orpheus emits SNAC audio-codec tokens which a SNAC vocoder decodes to 24 kHz
mono PCM. Prompt format is {voice}: {text}; the voice is a literal text
prefix learned at training time, so this model has no zero-shot cloning and
takes no audio input.
Audio token layout: control tokens 128257-128262, audio offset 128266,
7 tokens per frame each offset by (position_in_frame 0-6) * 4096.
Inference
Recommended sampling: temperature=0.3, repetition_penalty=1.3.
Output is quiet (peaks ~0.2-0.4) -- peak-normalise or level it downstream.
Licence and provenance
Derived from the SYSPIN Telugu corpus. The mirror this was trained from does not declare a licence; anyone intending commercial use should confirm terms with the upstream corpus holders (IISc SPIRE Lab / Bhashini) rather than relying on this repo.